code: def get_pipeline_info(pipeline):
      """Function print info about pipeline and return operations in it and depth
  
      :param pipeline: pipeline to process
      :return obtained_operations: operations in the nodes
      :return depth: depth of the pipeline
      """
  
      obtained_operations = [str(node) for node in pipeline.nodes]
      depth = int(pipeline.depth)
      pipeline.print_structure()
  
      return obtained_operations, depth
  
file_path: FEDOT/cases/river_levels_prediction/river_level_case_composer.py
imports: import datetime
  import warnings
  import numpy
  import pandas
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from sklearn.metrics import mean_absolute_error, mean_squared_error
  from golem.core.optimisers.genetic.gp_params import GPAlgorithmParameters
  from fedot.core.composer.composer_builder import ComposerBuilder
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.pipeline_composer_requirements import PipelineComposerRequirements
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.metrics_repository import RegressionMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
label_desc: Use image node_id 1 for calling a global function with example usage: get_pipeline_info(pipeline) and returns: obtained_operations,  depth